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Me, Myself, and AI: A New Podcast on Artificial Intelligence in Business



Why do only 10% of companies succeed with AI? For four years, BCG and MIT SMR have studied corporate adoption of artificial intelligence. The most recent research has found that 90% of organizations do not realize significant financial benefit from the technology. So, what are the other 10% doing right? Each episode of Me, Myself, and AI features a discussion with a leading practitioner helping his or her organization gain measurable value from AI.

In the 13th episode of the Me, Myself, and AI podcast, PepsiCo’s Colin Lenaghan discusses the role of Artificial Intelligence in the company’s pricing strategy and ongoing digital transformation. Listen to our podcast series below to find out.

More on Me, Myself, and AI: Whether they work at a born-digital organization or (more often) a legacy company, our guests all have actionable insights to share. The series covers strategy, deployment, human-and-machine collaboration, and scaling. We also explore what first interested these leaders in AI, how they got to where they are today, and what keeps them excited about their field.

Enjoy Me, Myself, and AI here or subscribe to the podcast on any of these platforms below to get the latest episode.

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Episode 13: No Need for AI Unicorns: PepsiCo’s Colin Lenaghan

Colin Lenaghan’s nearly 25-year career at PepsiCo has led him to a role overseeing strategic artificial intelligence initiatives in the company’s revenue management group. In this episode of the Me, Myself, and AI podcast, Lenaghan shares his thoughts on dealing with cultural change, the types of AI skills and competencies organizations should cultivate, and the digital transformation projects that keep him learning every day.

Episode 12: DIY With AI: The Home Depot’s Huiming Qu

In this episode of the Me, Myself, and AI podcast, Huiming Qu, senior director of data science at The Home Depot, discusses the reward mechanisms that motivate development teams, the importance of iteration to quickly solve large problems, and how machine learning and artificial intelligence help customers execute their home improvement projects.

Episode 11: Prototypes, Pilots, and Polymers: Cooper Standard’s Chris Couch

Automotive supplier Cooper Standard is using AI to improve technologies consumers take for granted in their everyday lives. In this episode of Me, Myself, and AI, Chris Couch, senior vice president and CTO at Cooper Standard, describes the company’s open innovation initiatives and commitment to employee engagement as it deploys and scales its AI solutions.

Episode 10: Designing for a Better Future: Mastercard’s JoAnn Stonier

In this episode of the Me, Myself, and AI podcast, JoAnn Stonier, chief data officer at Mastercard, explains how acknowledging that data sets may contain biased information can be the first step in mitigating biased outcomes. Stonier also discusses how design thinking can help leaders think of challenges related to artificial intelligence not just as problems but as constraints that can help them design better business solutions.

Episode 9: Learning, Engagement, and Empowerment: 1-800-Flowers’ Amit Shah

Amit Shah, president of 1-800-Flowers, describes the platform business’ approach to problem-solving with technologies like artificial intelligence and machine learning, highlights the importance of continuous learning to continually address new business problems, and explains why failure is an essential aspect of progress.

Episode 8: Games, Teams, and Moonshots: Google Cloud’s Will Grannis

Will Grannis has the unique challenge of leading a collective of chief technology officers at Google Cloud. Listen to this episode of the Me, Myself, and AI podcast, where he describes how he brings cross-functional teams together with customers to drive innovation in artificial intelligence and machine learning.

Episode 7: Less Algorithm, More Application: Lyft’s Craig Martell

Craig Martell, head of machine learning at Lyft, kicks off season two of the Me, Myself, and AI podcast with a discussion about bias, education, and the importance of cross-functional awareness throughout technology initiatives.

Episode 6: Tech and Ethics: The World Economic Forum’s Kay Firth-Butterfield on Doing the Right Thing in AI

“Companies want to go in doing the right thing”: Kay Firth-Butterfield, head of AI and machine learning at the World Economic Forum, discusses the balance of power and ethics in technology.

Episode 5: Fashion Forecasting: Arti Zeighami on Implementing AI at H&M

"It’s a combination of human and machine, the gut feeling and the data”: In this week’s episode of Me, Myself, and AI, Arti Zeighami, Chief Data and Analytics Officer of H&M Group, talks about implementing AI at a global retailer.

Episode 4: Better Together: Mattias Ulbrich on Combining Coffee, Business, and Technology at Porsche

“Collaboration between the machine and the person is very important”: In this week’s episode of MIT SMR and BCG’s Me, Myself, and AI podcast, Mattias Ulbrich, CIO of Porsche and CEO of Porsche Digital, talks about how AI can drive change in business, engineering, and society.

Episode 3: ‘The First Day Is the Worst Day’: DHL’s Gina Chung on How AI Improves Over Time

“With AI, the first day is the worst day”: Gina Chung, vice president of innovation at DHL, explains how AI enhances front-line operations, and the importance of human collaboration and buy-in on AI implementations.

Episode 2: Advancing Health Care With AI: Humana’s Slawek Kierner Talks Synthetic Data and Real Lives

“If you take a physician looking at health history of a synthetic individual, they cannot tell it’s unreal”: Slawek Kierner, senior vice president digital health and analytics at Humana, talks about using data simulations to predict real outcomes in this episode of MIT SMR and BCG’s Me, Myself, and AI podcast.

Are You Making the Most Out of Your Relationship with AI - Gradient

Are You Making the Most of Your Relationship with AI?

A recent BCG-MIT Sloan Management Review study suggests that in order to achieve significant financial benefits from their machines, companies will have to look beyond automation—and focus instead on learning and organizational transformation.

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